1. Field of the Invention
The present invention relates to computer systems and methods in which data resources are shared among concurrent data consumers while preserving data integrity and consistency relative to each consumer. More particularly, the invention concerns an implementation of a mutual exclusion mechanism known as “read-copy update” in a preemptive real-time computing environment. Still more particularly, the invention is directed to a technique for reducing performance degradation due to the preemption of non-real-time processes holding references to shared data that could otherwise be freed.
2. Description of the Prior Art
By way of background, read-copy update is a mutual exclusion technique that permits shared data to be accessed for reading without the use of locks, writes to shared memory, memory barriers, atomic instructions, or other computationally expensive synchronization mechanisms, while still permitting the data to be updated (modify, delete, insert, etc.) concurrently. The technique is well suited to multiprocessor computing environments in which the number of read operations (readers) accessing a shared data set is large in comparison to the number of update operations (updaters), and wherein the overhead cost of employing other mutual exclusion techniques (such as locks) for each read operation would be high. By way of example, a network routing table that is updated at most once every few minutes but searched many thousands of times per second is a case where read-side lock acquisition would be quite burdensome.
The read-copy update technique implements data updates in two phases. In the first (initial update) phase, the actual data update is carried out in a manner that temporarily preserves two views of the data being updated. One view is the old (pre-update) data state that is maintained for the benefit of operations that may be currently referencing the data. The other view is the new (post-update) data state that is available for the benefit of operations that access the data following the update. In the second (deferred update) phase, the old data state is removed following a “grace period” that is long enough to ensure that all executing operations will no longer maintain references to the pre-update data.
FIGS. 1A-1D illustrate the use of read-copy update to modify a data element B in a group of data elements A, B and C. The data elements A, B, and C are arranged in a singly-linked list that is traversed in acyclic fashion, with each element containing a pointer to a next element in the list (or a NULL pointer for the last element) in addition to storing some item of data. A global pointer (not shown) is assumed to point to data element A, the first member of the list. Persons skilled in the art will appreciate that the data elements A, B and C can be implemented using any of a variety of conventional programming constructs, including but not limited to, data structures defined by C-language “struct” variables.
It is assumed that the data element list of FIGS. 1A-1D is traversed (without locking) by multiple concurrent readers and occasionally updated by updaters that delete, insert or modify data elements in the list. In FIG. 1A, the data element B is being referenced by a reader r1, as shown by the vertical arrow below the data element. In FIG. 1B, an updater u1 wishes to update the linked list by modifying data element B. Instead of simply updating this data element without regard to the fact that r1 is referencing it (which might crash r1), u1 preserves B while generating an updated version thereof (shown in FIG. 1C as data element B′) and inserting it into the linked list. This is done by u1 acquiring an appropriate lock, allocating new memory for B′, copying the contents of B to B′, modifying B′ as needed, updating the pointer from A to B so that it points to B′, and releasing the lock. As an alternative to locking, other techniques such as non-blocking synchronization or a designated update thread could be used to serialize data updates. All subsequent (post update) readers that traverse the linked list, such as the reader r2, will see the effect of the update operation by encountering B′. On the other hand, the old reader r1 will be unaffected because the original version of B and its pointer to C are retained. Although r1 will now be reading stale data, there are many cases where this can be tolerated, such as when data elements track the state of components external to the computer system (e.g., network connectivity) and must tolerate old data because of communication delays.
At some subsequent time following the update, r1 will have continued its traversal of the linked list and moved its reference off of B. In addition, there will be a time at which no other reader process is entitled to access B. It is at this point, representing expiration of the grace period referred to above, that u1 can free B, as shown in FIG. 1D.
FIGS. 2A-2C illustrate the use of read-copy update to delete a data element B in a singly-linked list of data elements A, B and C. As shown in FIG. 2A, a reader r1 is assumed be currently referencing B and an updater u1 wishes to delete B. As shown in FIG. 2B, the updater u1 updates the pointer from A to B so that A now points to C. In this way, r1 is not disturbed but a subsequent reader r2 sees the effect of the deletion. As shown in FIG. 2C, r1 will subsequently move its reference off of B, allowing B to be freed following expiration of the grace period.
In the context of the read-copy update mechanism, a grace period represents the point at which all running processes having access to a data element guarded by read-copy update have passed through a “quiescent state” in which they can no longer maintain references to the data element, assert locks thereon, or make any assumptions about data element state. By convention, for operating system kernel code paths, a context (process) switch, an idle loop, and user mode execution all represent quiescent states for any given CPU (as can other operations that will not be listed here).
In FIG. 3, four processes 0, 1, 2, and 3 running on four separate CPUs are shown to pass periodically through quiescent states (represented by the double vertical bars). The grace period (shown by the dotted vertical lines) encompasses the time frame in which all four processes have passed through one quiescent state. If the four processes 0, 1, 2, and 3 were reader processes traversing the linked lists of FIGS. 1A-1D or FIGS. 2A-2C, none of these processes having reference to the old data element B prior to the grace period could maintain a reference thereto following the grace period. All post grace period searches conducted by these processes would bypass B by following the links inserted by the updater.
There are various methods that may be used to implement a deferred data update following a grace period, including but not limited to the use of callback processing as described in commonly assigned U.S. Pat. No. 5,727,209, entitled “Apparatus And Method For Achieving Reduced Overhead Mutual-Exclusion And Maintaining Coherency In A Multiprocessor System Utilizing Execution History And Thread Monitoring.”
The callback processing technique contemplates that an updater of a shared data element will perform the initial (first phase) data update operation that creates the new view of the data being updated, and then specify a callback function for performing the deferred (second phase) data update operation that removes the old view of the data being updated. The updater will register the callback function (hereinafter referred to as a “callback”) with a read-copy update subsystem so that it can be executed at the end of the grace period. The read-copy update subsystem keeps track of pending callbacks for each processor and monitors per-processor quiescent state activity in order to detect when each processor's current grace period has expired. As each grace period expires, all scheduled callbacks that are ripe for processing are executed.
Conventional grace period processing faces challenges in a preemptive realtime computing environment because a low priority reader holding a reference to shared data can be preempted by a higher priority process or blocked from acquiring a lock while in the read-side critical section. If the reader remains preempted or blocked for an extended period of time, grace periods cannot proceed and callbacks will not be processed. This can result in out-of-memory situations, which in turn can prevent high priority real-time processes from proceeding. A technique is therefore needed so that the priority of a preempted or blocked reader can be boosted, which would cause the reader to be scheduled ahead of other processes and complete its read-side critical section. This would allow grace-period processing to continue, eventually freeing memory and thereby permitting high-priority realtime processes to proceed without resource starvation.
Unfortunately, there might be a large number of reader processes potentially residing in a read-side critical section and a question arises as to how to identify preempted readers in an efficient manner. Scanning a data processing system's full list of processes is not an attractive solution because such scanning can be time-consuming and could potentially prevent high priority realtime processes from meeting their scheduling deadlines. Scanning only reader processes would be a better approach. However, creating and maintaining a list of each reader process that is currently within a read-side critical section is problematic. For example, such a list would require the use of expensive atomic instructions, spinlocks, and/or memory barriers within the RCU fast-path code used in preemptive realtime systems when readers enter and exit their critical sections (e.g., the rcu_read_lock( ) and rcu_read_unlock( ) primitives of the Linux® Kernel). Moreover, only a small fraction of read processes residing in a read-side critical section will normally be responsible for holding up current grace period processing as a result of being preempted or blocked. The vast majority of such readers will not be disturbed. Thus, a scan of even a reader process list would also waste valuable CPU time and degrade realtime latencies.
Accordingly, there is an unsolved need for a priority-boosting technique that overcomes the foregoing problems. What is needed is a solution that efficiently boosts the priority of only those readers that are holding up current grace period processing without having to scan large numbers of extraneous processes and without needing expensive operations within the common-case code paths of existing RCU primitives.